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In order to establish a connection between the ballistic performance and mechanical properties of armor steel, a ballistic simulation model was developed and subsequently validated for accuracy and reliability. The mechanical properties of the target plate were described using the Johnson–Cook constitutive relation. An analysis was conducted to investigate the impact of the J–C parameters of the target plate on its ballistic performance, revealing a strong linear relationship between them. Subsequently, a mathematical model represented as H = 14.82 − 0.0048A − 0.0023B + 5.95n − 81.3C was derived, and its accuracy was demonstrated to exceed 90%. This mathematical model can effectively predict the ballistic performance of the armor steel, even when its mechanical properties undergo variations during the production process. This prediction capability significantly contributes to reducing research costs and time.

To enhance the hydrogen storage performance of Mg-Ni system alloys, multi-elemental alloys incorporating Y element, namely Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3), were synthesized through ball milling and sintering. The microstructures of Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3) alloys were characterized using XRD and SEM/EDS techniques, and the hydrogen storage properties of Mg2Ni0.9Co0.1 and Mg1.7Y0.3Ni0.9Co0.1 alloys were evaluated via the Sieverts method. At a sintering temperature of 500 °C, the Y element existed in the form of Y/Y2O3 phases and displayed no reactivity with other alloy constituents. The addition of Y enhanced the activation performance of Mg-Ni system alloys, because it takes 2 times for Mg1.7Y0.3Ni0.9Co0.1 alloy to complete activation, while Mg2Ni0.9Co0.1 needs 3, albeit causing a slight reduction from 3.6 wt% to 3.2 wt% in the hydrogen storage capacity when Y replaced Mg. The enthalpy of hydrogen desorption of Mg1.7Y0.3Ni0.9Co0.1 alloy was 57.4 kJ mol−1 H2, which was significantly lower than that of Mg2Ni0.9Co0.1 (68.0 kJ mol−1 H2) and Mg2Ni alloy (64.4 kJ mol−1 H2), indicating improved thermodynamic properties. Moreover, the apparent activation energy of Mg2Ni0.9Co0.1 (71.48 kJ mol−1 H2) was lower than that of Mg1.7Y0.3Ni0.9Co0.1 (83.62 kJ mol−1 H2), implying that the addition of Y reduced the kinetic properties.

To improve the surface properties of 5083 aluminum, Al0.8FeCrCoNiCu0.5Yx (x = 0, 0.05, 0.1, and 0.2) high-entropy alloy coatings were prepared by laser cladding. The phase structure and microstructure of the Al0.8FeCrCoNiCu0.5Yx coatings were characterized by XRD and SEM. The tribological properties of the coating were tested by a friction and wear tester. An electrochemical workstation tested the corrosion resistance of the coating. The results show that when Y content is less than 0.2, the Al0.8FeCrCoNiCu0.5Yx coating is in the FCC1, BCC1, and BCC2 phases. When Y is added to 0.2, the coating appears rich in the Y phase. With the increased Y content, the hardness of the coating can increase. The average hardness of Y0, Y0.05, Y0.1, and Y0.2 are 479HV0.2, 517HV0.2, 532HV0.2, and 544HV0.2, respectively. Microstructure evolution leads to an increase in the hardness of the coating. The effect of Y on the wear resistance of the Al0.8FeCrCoNiCu0.5Yx coatings is consistent with the hardness. Al0.8FeCrCoNiCu0.5Y0.2 coating has the lowest wear rate, at is 8.65 × 10−6 mm3/Nm. The corrosion current density of Al0.8FeCrCoNiCu0.5Y0.05 and Al0.8FeCrCoNiCu0.5Y0.1 coatings is in the order of 10−8, which is less than Al0.8FeCrCoNiCu0.5Y0.2 and Al0.8FeCrCoNiCu0.5. The performance of each component coating is superior to that of the substrate.

First-principles density-functional theory was used to analyze the effects of Al on the mechanical properties, stability, elastic constant, and elastic anisotropy of AlxCrFeCoNiCu (x = 0, 0.5, 1, 1.5, 2) HEAs. The calculations of volume modulus, shear modulus, and Young’s modulus show that the increase of Al content can improve the strength of HEAs, and the degree of influence of Al on Young’s modulus of the HEAs is higher than that of shear modulus and volume modulus. The calculations of Cauchy pressure, Paugh ratio, and Poisson’s ratio show that FeCoNiCrCu, Al0.5CrFeCoNiCu, and AlCrFeCoNiCu have good flexibility and plasticity. AlxCrFeCoNiCu HEAs with different Al contents all exhibit elastic anisotropy.

To enhance the hydrogen storage performance of Mg-Ni system alloys, multi-elemental alloys incorporating Y element, namely Mg 2-x Y x Ni 0.9 Co 0.1 (x = 0, 0.1, 0.2, 0.3), were synthesized through ball milling and sintering. The microstructures of Mg 2-x Y x Ni 0.9 Co 0.1 (x = 0, 0.1, 0.2, 0.3) alloys were characterized using XRD and SEM/EDS techniques, and the hydrogen storage properties of Mg 2 Ni 0.9 Co 0.1 and Mg 1.7 Y 0.3 Ni 0.9 Co 0.1 alloys were evaluated via the Sieverts method. At a sintering temperature of 500 °C, the Y element existed in the form of Y/Y 2 O 3 phases and displayed no reactivity with other alloy constituents. The addition of Y enhanced the activation performance of Mg-Ni system alloys, because it takes 2 times for Mg 1.7 Y 0.3 Ni 0.9 Co 0.1 alloy to complete activation, while Mg 2 Ni 0.9 Co 0.1 needs 3, albeit causing a slight reduction from 3.6 wt% to 3.2 wt% in the hydrogen storage capacity when Y replaced Mg. The enthalpy of hydrogen desorption of Mg 1.7 Y 0.3 Ni 0.9 Co 0.1 alloy was 57.4 kJ mol −1 H 2 , which was significantly lower than that of Mg 2 Ni 0.9 Co 0.1 (68.0 kJ mol −1 H 2 ) and Mg 2 Ni alloy (64.4 kJ mol −1 H 2 ), indicating improved thermodynamic properties. Moreover, the apparent activation energy of Mg 2 Ni 0.9 Co 0.1 (71.48 kJ mol −1 H 2 ) was lower than that of Mg 1.7 Y 0.3 Ni 0.9 Co 0.1 (83.62 kJ mol −1 H 2 ), implying that the addition of Y reduced the kinetic properties.

To improve the surface properties of 5083 aluminum, Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.x] (x = 0, 0.05, 0.1, and 0.2) high-entropy alloy coatings were prepared by laser cladding. The phase structure and microstructure of the Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.x] coatings were characterized by XRD and SEM. The tribological properties of the coating were tested by a friction and wear tester. An electrochemical workstation tested the corrosion resistance of the coating. The results show that when Y content is less than 0.2, the Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.x] coating is in the FCC1, BCC1, and BCC2 phases. When Y is added to 0.2, the coating appears rich in the Y phase. With the increased Y content, the hardness of the coating can increase. The average hardness of Y[sub.0] , Y[sub.0.05] , Y[sub.0.1] , and Y[sub.0.2] are 479HV[sub.0.2] , 517HV[sub.0.2] , 532HV[sub.0.2] , and 544HV[sub.0.2] , respectively. Microstructure evolution leads to an increase in the hardness of the coating. The effect of Y on the wear resistance of the Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.x] coatings is consistent with the hardness. Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.0.2] coating has the lowest wear rate, at is 8.65 × 10[sup.−6] mm[sup.3] /Nm. The corrosion current density of Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.0.05] and Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.0.1] coatings is in the order of 10[sup.−8] , which is less than Al[sub.0.8] FeCrCoNiCu[sub.0.5] Y[sub.0.2] and Al[sub.0.8] FeCrCoNiCu[sub.0.5] . The performance of each component coating is superior to that of the substrate.

Small extracellular vesicles (sEVs) derived from gastric juice (GJ) have emerged as potential biomarkers for gastric disease. However, methods for isolating sEVs from GJ (gsEVs) remain underexplored. This study employed four methods for isolating gsEVs: ultracentrifugation (UC), PEG6000 precipitation combined with UC (PEG-UC), UC combined with size exclusion chromatography (UC-SEC), and ultrafiltration combined with SEC (UF-SEC). The yield and purity of gsEVs isolated by each method were evaluated, and the proteomic profile of gsEVs was examined through label-free quantitative proteomics. Additionally, a series of validation experiments were conducted to identify specific biomarkers for gsEVs. The results revealed that gsEVs isolated using the UC method exhibited the highest purity and the largest number of identified proteins compared to the other methods. Notably, the gastric tissue-specific peptide trefoil factor 2 (TFF2) was highly expressed in gsEVs isolated by all methods, suggesting that TFF2 may serve as a specific biomarker for gsEVs. Validation experiments showed that TFF2 was exclusively present in gsEVs and not in the GJ supernatant after UC. Furthermore, TFF2 was selectively expressed in gsEVs, but not in sEVs derived from other biofluids such as intestinal juice and plasma. The efficiency of TFF2 as a gsEVs biomarker was higher than the commonly used biomarker CD9, CD81, and Syntenin-1. Multi-omics analysis indicated that the functions of gsEVs carrying TFF2 were primarily associated with inflammation and cancer. The UC method is suitable for isolating gsEVs, particularly for mass spectrometry-based proteomic analysis. The small peptide TFF2 may serve as a potential specific biomarker for gsEVs. This study offers new insights for research on sEVs in gastric diseases.

EtherCAT, known for its exceptional real-time performance and synchronization capabilities, is widely used in industrial multi-axis control systems. In these systems, the synchronization status of slave axes plays a critical role in determining the precision of the end-effector. While the distributed clock synchronization technology in EtherCAT achieves effective overall synchronization for the master–slave system, notable synchronization errors persist between non-reference slaves and the reference slave. To address this issue, this paper proposes an improved EtherCAT master–slave synchronization method based on the Double Exponential Smoothing (DES) algorithm. The proposed method begins by measuring the transmission delay between the master and the reference slave. Using this delay, the exponential moving average technique is applied to periodically adjust and compensate for synchronization errors between the master and the reference slave. Subsequently, the DES algorithm is employed to periodically calculate the clock drift of non-reference slave clocks relative to the reference clock, enabling corresponding compensation for the slave clocks. To validate the feasibility of the proposed method, an EtherCAT master–slave experimental platform was established using the Xenomai real-time operating system, and synchronization performance was evaluated. Experimental results show that the proposed method controls synchronization errors within ±90 ns in a six-slave experimental setup. Compared with synchronization error ranges achieved using only exponential moving average (EMA) for clock drift compensation, the proposed method reduces the synchronization error by approximately 16.36%, thereby validating its effectiveness.

Introduction This study aimed to understand the impact of the coronavirus disease 2019 (COVID-19) epidemic on the distribution and antibiotic resistance of pathogenic bacteria isolated from the lower respiratory tract of children in our hospital. Methods Antimicrobial susceptibility tests were performed on bacteria isolated clinically from the lower respiratory tracts of children in our hospital from 2018 to 2021 by the Kirby–Bauer method and automated systems. Results From 2018 to 2021, the top three lower respiratory tract clinical isolates in our hospital were Streptococcus pneumoniae , Moraxella catarrhalis , and Haemophilus influenzae . These three species showed obvious seasonal epidemic patterns, and their numbers decreased significantly during the COVID-19 epidemic, from 4559 in 2019 to 1938 in 2020. Bacterial resistance to antibiotics also changed before and after the COVID-19 epidemic. The annual proportions of methicillin-resistant S. aureus (MRSA) were 41%, 37.4%, 26.2%, and 29.8%. The resistance rates of Klebsiella pneumoniae to ceftriaxone were 40.5%, 51.9%, 35.3%, and 53.3%, and the detection rates of carbapenem-resistant K. pneumoniae (CRKP) were 2.7%, 11.1%, 5.9%, and 4.4%. The detection rates of β-lactamase-producing H. influenzae were 51.9%, 59.2%, 48.9%, and 55.3%. The rate of MRSA, ceftriaxone-resistant K. pneumoniae , CRKP, and β-lactamase-producing H. influenzae decreased significantly in 2020 compared with 2019, whereas that of carbapenem-resistant P. aeruginosa and carbapenem-resistant A. baumannii increased. The detection rates of β-lactamase-negative ampicillin-resistant H. influenzae (BLNAR) gradually increased over the 4 years. Conclusions Protective measures against COVID-19, including reduced movement of people, hand hygiene, and surgical masks, may block the transmission of S. pneumoniae , H. influenzae , and M. catarrhalis and reduce the detection rate of MRSA, ceftriaxone-resistant K. pneumoniae , CRKP, and β-lactamase-producing H. influenzae .